code: def clean_events(
      events: DataframeLike,
      defs: HyperBindings,
      engine: Engine,
      npartitions: Optional[int] = None,
      chunksize: Optional[int] = None,
      dropna: bool = False,  # FIXME https://github.com/rapidsai/cudf/issues/7735
      debug: bool = False,
  ) -> DataframeLike:
      """
      Copy with reset index and in the target engine format
      """
      logger.debug("@clean: %s", events.dtypes)
  
      # FIXME https://github.com/rapidsai/cudf/issues/7735
      # None -> np.nan
      custom_event_id_flag = False
      if (engine in [Engine.DASK, Engine.DASK_CUDF]) and (
          defs.event_id not in events.columns
      ):
          events[defs.event_id] = range(0, len(events))
          custom_event_id_flag = True
      if dropna and (engine == Engine.DASK_CUDF):
          import cudf, numpy as np
  
          if isinstance(
              events, pd.DataFrame
          ):  # or isinstance(events, cudf.DataFrame):
              events = events.copy()
              for c in events.columns:
                  if (
                      events[c].dtype.name == "object"
                      and events[c].isna().any()
                  ):
                      logger.debug(
                          "None -> nan workaround for col [ %s ] => %s",
                          c,
                          events[c],
                      )
                      events[c] = events[c].fillna(np.nan)
                      logger.debug(
                          "... with drop: %s", events[c].dropna()
                      )
      out_events = df_coercion(
          events, engine, npartitions, chunksize, debug
      )
      if debug and (engine in [Engine.DASK, Engine.DASK_CUDF]):
          out_events = out_events.persist()
          logger.debug("coerced events: %s", out_events.compute())
  
      if engine in [Engine.CUDF, Engine.DASK_CUDF]:
          for c in out_events:
              if out_events[c].dtype.name == "timedelta64[ns]":
                  logger.debug(
                      "timedelta concats may conflict when nans; coerce col [ %s ] => str",
                      c,
                  )
                  out_events[c] = out_events[c].astype(str)
  
      out_events = shallow_copy(out_events, engine)
  
      out_events = out_events.reset_index(drop=True)
      if debug and (engine in [Engine.DASK, Engine.DASK_CUDF]):
          out_events = out_events.persist()
          logger.debug("copied events: %s", out_events.compute())
      if (defs.event_id in events.columns) or custom_event_id_flag:
          out_events[defs.event_id] = (
              defs.event_id + defs.delim
          ) + out_events[defs.event_id].astype(str).fillna(
              defs.null_val
          )
      else:
          out_events[defs.event_id] = (
              defs.event_id + defs.delim
          ) + out_events[[]].reset_index()["index"].astype(str)
  
      if debug and (engine in [Engine.DASK, Engine.DASK_CUDF]):
          out_events = out_events.persist()
          logger.debug("tagged events: %s", out_events.compute())
          logger.debug("////clean_events")
      logger.debug("////clean: %s", out_events.dtypes)
      return out_events
  
imports: from typing import TYPE_CHECKING, Any, Dict, List, Optional
  from .Engine import Engine, DataframeLike, DataframeLocalLike
  import numpy, pandas, pyarrow, sys
  from .util import setup_logger
label_desc: Use image node_id 21 for calling a global function with example usage: clean_events(events, defs, engine, npartitions, chunksize, dropna, debug) and returns: out_events